在光伏系统中在部分遮阳条件下,基于斑马优化算法有效的MPPT的实验验证
Feriel Abdelmalek1, Hamza Afghoul2, Fateh Krim1
1LEPCI laboratory, Department of Electronics, Faculty of Technology, University of Ferhat Abbas Setif 1, Sétif, Algeria.
Scientific reports
|October 30, 2024
概括
一个新的斑马优化算法 (ZOA) 有效地跟踪光伏 (PV) 系统中的全球最大功率点 (GMPP). 这种方法在部分和动态阴影条件中表现出色,比现有算法提供更高的性能.
科学领域:
- 电气工程 电气工程
- 可再生能源系统可再生能源系统
- 优化算法 优化算法
背景情况:
- 光伏 (PV) 系统需要高效的最大功率点跟踪 (MPPT) 才能获得最佳的能源收获.
- 部分遮阳条件 (PSC) 和动态遮阳条件 (DSC) 显著降低了光伏系统的性能.
- 现有的MPPT算法在复杂的阴影场景下实现快速和准确的跟踪方面面临挑战.
研究的目的:
- 引入和评估斑马优化算法 (ZOA) 用于全球最大功率点 (GMPP) 在光伏系统中的跟踪.
- 评估ZOA在处理具有挑战性的部分遮阳条件 (PSC) 和动态遮阳条件 (DSC) 的有效性.
- 为了比较ZOA的性能与已建立的MPPT算法,如GWO,PSO,FPA和WOA.
主要方法:
- 模拟光伏系统使用块查找表进行高效分析.
- 为GMPP跟踪实施和应用斑马优化算法 (ZOA).
- 在各种阴影条件下对ZOA与GWO,PSO,FPA和WOA进行比较性能分析.
- 使用DSPACE板和光伏模拟器进行实验验证.
主要成果:
- 在PSC下,ZOA实现了0.875秒的平均追踪时间和99.95%的追踪效率.
- 与其他算法相比,ZOA显示了高达2%的跟踪效率和更快的融合 (10-15%更快).
- ZOA显著减少了运行点的变化,并在不同的阴影条件下显示出更强的弹性.
- 实验结果证实了ZOA在现实世界光伏系统模拟中的高效率和可靠性.
结论:
- 斑马优化算法 (ZOA) 为光伏系统提供了一个高效和可靠的MPPT解决方案.
- ZOA有效地克服了严重的部分和动态阴影条件所带来的挑战.
- 与现有的MPPT算法相比,ZOA在跟踪速度,效率和稳定性方面提供了显著的优势.
关键词:
全球最大功率点 (GMPP)当地最大功率点 (LMPP)最大的功率点跟踪 (MPPT)部分遮阳条件 (PSCs) 部分遮阳条件太阳能 (PV) 系统 光伏 (PV) 系统斑马优化算法 (ZOA) 的使用更多相关视频
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